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Data-driven simulation and control

Data-driven simulation and control
Data-driven simulation and control
Classical linear time-invariant system simulation methods are based on a transfer function, impulse response, or input/state/output representation. We present a method for computing the response of a system to a given input and initial conditions directly from a trajectory of the system, without explicitly identifying the system from the data. Similarly to the classical approach for simulation, the classical approach for control is model-based: first a model representation is derived from given data of the plant and then a control law is synthesized using the model and the control specifications. We present an approach for computing a linear quadratic tracking control signal that circumvents the identification step. The results are derived assuming exact data and the simulated response or control input is constructed off-line.
0020-3270
1946-1959
Markovsky, Ivan
7d632d37-2100-41be-a4ff-90b92752212c
Rapisarda, Paolo
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
Markovsky, Ivan
7d632d37-2100-41be-a4ff-90b92752212c
Rapisarda, Paolo
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b

Markovsky, Ivan and Rapisarda, Paolo (2008) Data-driven simulation and control. International Journal of Control, 81 (12), 1946-1959.

Record type: Article

Abstract

Classical linear time-invariant system simulation methods are based on a transfer function, impulse response, or input/state/output representation. We present a method for computing the response of a system to a given input and initial conditions directly from a trajectory of the system, without explicitly identifying the system from the data. Similarly to the classical approach for simulation, the classical approach for control is model-based: first a model representation is derived from given data of the plant and then a control law is synthesized using the model and the control specifications. We present an approach for computing a linear quadratic tracking control signal that circumvents the identification step. The results are derived assuming exact data and the simulated response or control input is constructed off-line.

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More information

Published date: December 2008
Additional Information: simulation, data-driven control, output matching, linear quadratic tracking, system identification.
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 263423
URI: http://eprints.soton.ac.uk/id/eprint/263423
ISSN: 0020-3270
PURE UUID: 59df51cb-1ae9-4bcb-b80b-12563e391210

Catalogue record

Date deposited: 14 Feb 2007
Last modified: 14 Mar 2024 07:31

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Contributors

Author: Ivan Markovsky
Author: Paolo Rapisarda

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